Importance of different facial parts for face detection networks

P Hofer, M Roland, P Schwarz… - … on Biometrics and …, 2021 - ieeexplore.ieee.org
Most state-of-the-art face detection algorithms are usually trained with full-face pictures,
without any occlusions. The first novel contribution of this paper is an analysis of the …
被引用次数：17 相关文章
[PDF] mroland.at

[PDF][PDF] Importance of different facial parts for face detection networks

P Hofer, M Roland, P Schwarz, M Schwaighofer… - mroland.at
Most state-of-the-art face detection algorithms are usually trained with full-face pictures,
without any occlusions. The first novel contribution of this paper is an analysis of the …
[PDF] researchgate.net

[PDF][PDF] Importance of different facial parts for face detection networks

P Hofer, M Roland, P Schwarz, M Schwaighofer… - researchgate.net
Most state-of-the-art face detection algorithms are usually trained with full-face pictures,
without any occlusions. The first novel contribution of this paper is an analysis of the …
[PDF] digidow.eu

[PDF][PDF] Importance of different facial parts for face detection networks

P Hofer, M Roland, P Schwarz, M Schwaighofer… - digidow.eu
Most state-of-the-art face detection algorithms are usually trained with full-face pictures,
without any occlusions. The first novel contribution of this paper is an analysis of the …